/*
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 *    Prediction.java
 *    Copyright (C) 2002 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers.evaluation;

/**
 * Encapsulates a single evaluatable prediction: the predicted value plus the
 * actual class value.
 * 
 * @author Len Trigg (len@reeltwo.com)
 * @version $Revision: 1.7 $
 */
public interface Prediction {

	/**
	 * Constant representing a missing value. This should have the same value as
	 * weka.core.Instance.MISSING_VALUE
	 */
	double MISSING_VALUE = weka.core.Instance.missingValue();

	/**
	 * Gets the weight assigned to this prediction. This is typically the weight
	 * of the test instance the prediction was made for.
	 * 
	 * @return the weight assigned to this prediction.
	 */
	double weight();

	/**
	 * Gets the actual class value.
	 * 
	 * @return the actual class value, or MISSING_VALUE if no prediction was
	 *         made.
	 */
	double actual();

	/**
	 * Gets the predicted class value.
	 * 
	 * @return the predicted class value, or MISSING_VALUE if no prediction was
	 *         made.
	 */
	double predicted();

}
